A facade to the actual RandomGenerator.
In previous versions, Random was a very bad fallback random generator,
with an included warning, to not use it.
Now this old generator was renamed to RandomGNUSmalltalk,
and the default generator used is the one provided by the much
better RandomGenerator class.
Random new next:10

return the next random number in the range 0..1
This method behaves like the corresponding instance method,
but allows generation of random numbers without
a need for an instance of Random to be kept around.
This uses a common, shared generator.

return a random number between start and stop.
This method behaves like the corresponding instance method,
but allows generation of random numbers without
a need for an instance of Random to be kept around.
This uses a common, shared generator.

return a boolean random.
This method behaves like the corresponding instance method,
but allows generation of random numbers without
a need for an instance of Random to be kept around.
This uses a common, shared generator.

return an integral random number.
This method behaves like the corresponding instance method,
but allows generation of random numbers without
a need for an instance of Random to be kept around.
This uses a common, shared generator.

return an integral random number between start and stop.
This method behaves like the corresponding instance method,
but allows generation of random numbers without
a need for an instance of Random to be kept around.
This uses a common, shared generator.

return a number useful for seeding.
This takes the current processor's time, plus the processor's process id,
plus some value depending on the memory allocation state,
plus a random salt, and shuffles those bits around.
The entropy returned should be reasonable enough for a good seed of a good rnd
generator. However, keep in mind, that it only has a limited number of entropy bits
(in the order of 32).
But it should be much better than what is commonly used in older
programs (current time) or even a constant.

Chi-Squared Test - from R.Sedgewick's 1st ed. of 'Algorithms',
o N = number of samples
o r = range of random numners is [0,r) -- condition: N >= 10r.
o Random number generator 'passes' if chisquare value is very close to r
o Repeat test several times, since it may be *wrong* 1 out of 10 trials.

set the initial seed value based on the current time and processId.
These numbers implement a maximum period generator which passes
the spectral test for randomness for dimensions 2 3 4 5 6 and
the product does not overflow 2 raisedTo:29.

Use both time and processId for seed, to make different processes
return different Random numbers